---
name: ai-agents
description: "AI Agents: 18 concepts, no maths assumed."
version: 1.0.0
author: Learn AI
license: CC-BY-4.0
metadata:
  hermes:
    tags: [Ai, Agents]
    related_skills: [llms-and-generative-ai, machine-learning]
    source: https://basavapurushottam.com/learn-ai
---
# AI Agents

18 concepts, written for an adult with no computer science and no mathematics past school arithmetic. Each concept is a file under `references/`; load one when it is the thing being asked about rather than reading the whole domain.


## When to Use

- The reader asks about ai agents and wants it explained from the ground up rather than summarised.

- A term below comes up and you want the plain-language account of it, with a worked example.

- You need to know what a concept rests on before teaching it — every reference lists its prerequisites.


## When NOT to Use

- The reader wants current events, papers or library documentation. This is a curriculum, not a news source, and it does not update itself.

- The reader wants code they can ship. Examples here are written to be understood, not deployed.


## How to Run

Open the file listed beside a concept in Quick Reference below. The files live in the `references` directory, are plain Markdown with no front matter and no dependencies — read the one you want and ignore the rest.


## Quick Reference


### AI Agents

- `references/agent-cards.md` — **Agent Cards**: Machine-readable descriptions of an agent's identity, capabilities and interfaces, so o…
- `references/agent-communication-protocols.md` — **Agent Communication Protocols**: Standards for agents to exchange messages, delegate tasks and share results across syst…
- `references/agent-executors.md` — **Agent Executors**: The runtime that drives the agent loop — dispatching tool calls, managing state, enforc…
- `references/agent-loop.md` — **Agent Loop**: The cycle at the heart of every agent: receive context, decide an action, execute it, o…
- `references/agent-memory-systems.md` — **Agent Memory Systems**: The stores an agent reads and writes across turns — working context, episodic history,…
- `references/analyst-agents.md` — **Analyst Agents**: Agents built for research and analysis workflows — gathering sources, extracting eviden…
- `references/conversation-state.md` — **Conversation State**: What the system remembers and re-sends across turns — history, summaries, extracted fac…
- `references/conversational-agents.md` — **Conversational Agents**: Dialogue systems maintaining coherent multi-turn interaction, tracking state and intent…
- `references/escalation-workflows.md` — **Escalation Workflows**: Defined paths for handing a case to a human or a higher-authority process when confiden…
- `references/routing-and-expert-specialization.md` — **Routing and Expert Specialization**: Directing each request to the most appropriate model, tool or specialised agent rather…
- `references/subagents.md` — **Subagents**: Delegating a scoped task to a separate agent with its own context, returning only the r…

### AI Coding Assistants

- `references/agent-instruction-files.md` — **Agent Instruction Files**: Persistent repository files giving a coding agent standing context — conventions, archi…
- `references/agentic-test-authoring.md` — **Agentic Test Authoring**: Using agents to generate, maintain and repair test suites, driven from the application…
- `references/business-workflow-integration.md` — **Business Workflow Integration**: Connecting agents and skills into real business systems — CRM, ticketing, calendars, fi…
- `references/claude-skills.md` — **Claude Skills**: Packaged, reusable instructions that turn repeatable work into something invokable rath…
- `references/no-code-model-building.md` — **No-Code Model Building**: Building and deploying models through visual interfaces without writing code, lowering…
- `references/skill-design-and-scoping.md` — **Skill Design and Scoping**: Deciding what a skill covers and where it stops, which is the main craft in making one…

### Model Context Protocol

- `references/mcp-connectors.md` — **MCP Connectors**: Servers exposing tools, data and prompts over the Model Context Protocol so any compati…


## Pitfalls

- The concepts are ordered by what rests on what, not by difficulty. A later concept is not always harder; it is later because something else has to come first.

- Explanations avoid notation the reader has not met. If you reintroduce standard symbols, say what they mean, or you undo the thing this curriculum is for.


## Verification

`ls references/ | wc -l` should print 18.


---

From [Learn AI](https://basavapurushottam.com/learn-ai). Prose is licensed CC BY 4.0.
